Mun, Ju Hyoung Samsung Electronics juhyoung.mun@samsung.com Samsung Electronics
� Packet Classification is one of the major challenges for next generation routers ◦ Involves complicated multi-dimensional search ◦ Should be performed in wire-speed for every incoming packet � We proposed a new packet classification algorithm which applies binary search on length to the area-based quad-trie. Sa Samsun msung Ele g Electroni nics
� Area-based Quad-Trie (AQT) ◦ the most well known 2-dimensional search trie ◦ Rules are represented by rectangles in the source and destination prefix plane ◦ 2-Dimensional area of source and destination prefix is partitioned recursively ◦ Each partitioned area is mapped into a node of a Quad-trie � Crossing Filter Set ◦ If any dimension of a rule completely crosses the area, it is defined as a crossing filter. Sa Samsun msung Ele g Electroni nics
Ar e a - - Base d Quad Base d Quad- - T T r ie Ar e a r ie (Buddhikot, PHSN1999) (Buddhikot, PHSN1999) src prefix dst prefix Src Port Dst Port Prtl R0 0000* 1010* 53, 53 443, 443 17 R1 000111* 11110* 53, 53 25, 25 6 R2 101011* 001101* 53, 53 25, 25 17 R3 00000* 10100* 67, 67 5632 6 R4 000* 1110* 1024 1024 6 R5 0011* 00* 53, 53 25, 25 4 R6 110* 01* 0, 65535 5632 6 R7 110010* 1101100* 0, 65535 5632 6 R8 1010* 00110* 53, 53 25, 25 6 R9 11010* 110* 0, 15576 2783 4 R10 * 110* * * * Sa Samsun msung Ele g Electroni nics
destination R1 R4 R7 R10 R9 1 R0 R3 R6 0 R2 R8 R5 source 0 1 � AQT performs the linear search on prefix length, and so it does not provide good search performance. Samsun Sa msung Ele g Electroni nics
Binar y Se ar c h on L e ngth Binar y Se ar c h on L e ngth (Waldvoge l, Sigc omm1997) (Waldvoge l, Sigc omm1997) � Binary search for length � hash in accessing the actual prefix value of that length � Excellent search performance : O(log 2 W) ◦ W : maximum prefix length � Pre-computation is required ◦ Markers are required in empty internal nodes to indicate the existence of prefixes in longer lengths ◦ Best Matching Prefix (BMP) is noted with markers to avoid the back-tracking in case that markers mislead the search Sa Samsun msung Ele g Electroni nics
1-D Binary Search on Length 1-D Binary Search on Length very good search performance � 2-D Binary Search on Length 2-D Binary Search on Length 2-D Binary Trie 2-D Binary Trie Area-Based Quad-Trie � Sa Samsun msung Ele g Electroni nics
� Unlike IP address lookup, the Packet Classification looks for the highest priority rule among all matching rules ◦ Pre-computed markers and their best matching rules are not suitable for finding all matching rules � Why markers and their BMPs are required? ◦ Because of nesting relationship of prefixes ◦ If there is no nesting relationship, the pre-computation is not necessary � By removing the nesting relationship, we can remove the pre-computation Sa Samsun msung Ele g Electroni nics
� AQT trie is decomposed into multiple tries depending on the relative level � So that rules located in each decomposed trie never has nesting relation. � The number of tries would be equal to the maximum number of rule nesting ◦ But there are not many levels of rule nesting in classifiers Sa Samsun msung Ele g Electroni nics
� The data structure is composed of two tables ◦ A quad-trie table and a rule table � To build the quad-trie tables Build ( filter list ) do { root = Build_AQT_trie( filter list ); } while( filter != NULL ) n = 1; do { Leaves = delete_nth_level_enclosures_from_AQT_Trie( root ); delete_unnecessary_internal_nodes( root ); nth_table = Build_Hashtable( Leaves ); n++; } while( root != NULL ) Sa Samsun msung Ele g Electroni nics
� The rule table is generated as follows ◦ The number of entries of the rule table is the same as the number of rules. ◦ Each entry of the rule table has the rest of header fields ◦ If there is more than one rule mapped into a node, rules should be connected by a linked-list in the order of their priorities Sa Samsun msung Ele g Electroni nics
Search (input) BMF = *; MF = *; codeword = concatenation( src_address(input), dst_address(input) ) n = 1; //start at 1st hash table ptr = index( nth _table); do { CFS = BSL( ptr, codeword ); // search crossing filter set MF = Search_ruletable( CFS, input ); if ( MF is higher than BMF ) BMF = MF; n++; ptr = index( nth _table); } while (ptr ! = NULL) return BMF; Sa Samsun msung Ele g Electroni nics
� If rule priorities are considered, the performance improvement is expected. � Optimization Technique 1 ( Search Lower Priority Rules Later) ◦ From the analysis of rule distribution, we found out that rules with a wild-card in any of prefix fields have low priorities in general ◦ The first optimization technique is to search the trie composed of wild-card rules at the latest Sa Samsun msung Ele g Electroni nics
<Optimization Technique 1> Sa Samsun msung Ele g Electroni nics
� Optimization Technique 2 (Search Higher Priority Rules Earlier) ◦ From the further analysis, we found out that there is some correlation between the length of prefixes and the priority of rules ◦ Rules with longer prefixes tend to have higher priorities ◦ Therefore, if we search rules in lower levels first, the better search performance is expected Sa Samsun msung Ele g Electroni nics
<Optimization Technique 2> Sa Samsun msung Ele g Electroni nics
� Performance evaluation result of proposed algorithm (ClassBench, Infocom2005) Mtrie rie Mrule Mrul M/rul M/rule N Nt Nt Twst Twst Tavg Tavg (Kbyte) (Kbyte) (byte) ACL1k 958 5 47 21.3 23 20.2 45 ACL5k 4659 6 78 34.7 84.3 97.9 39 FW1k 870 3 293 192.7 3.5 18.3 25 FW5k 4343 3 1002 560.7 4.2 91.4 22 IPC1k 988 5 76 63.2 32.3 20.7 54 IPC5k 4467 5 263 182.3 25.5 93.8 27 Sa Samsun msung Ele g Electroni nics
� Performance evaluation result of proposed optimization technique 1 Mtrie rie Mrule Mrul M/rul M/rule N Nt Nt Twst Twst Tavg Tavg (Kbyte) (Kbyte) (byte) ACL1k 958 5 43 17.34 23 20.2 45 ACL5k 4659 6 59 20.10 84.3 97.9 39 FW1k 870 3 286 115.95 3.5 18.3 25 FW5k 4343 3 971 392.54 4.2 91.4 22 IPC1k 988 5 71 33.38 32.3 20.7 54 IPC5k 4467 5 233 65.18 25.5 93.8 27 Sa Samsun msung Ele g Electroni nics
� Performance evaluation result of proposed optimization technique 2 Mtrie rie Mrule Mrul M/rul M/rule N Nt Nt Twst Twst Tavg Tavg (Kbyte) (Kbyte) (byte) ACL1k 958 5 21 12.54 23.2 20.2 45 ACL5k 4659 6 39 17.91 93.8 97.9 41 FW1k 870 3 378 19.31 3.8 18.3 25 FW5k 4343 3 804 67.02 4.5 91.4 22 IPC1k 988 5 69 21.89 33.9 20.7 55 IPC5k 4467 5 234 32.30 24.5 93.8 27 Sa Samsun msung Ele g Electroni nics
� Performance comparison result for ACL types ACL1k ACL1k ACL5k ACL5k M M Tavg Tavg Twst Twst Tavg Tavg Twst Twst (Kbyte) (Kbyte) H-trie [1] 77.2 124 82.9 84.0 177 401.5 HiCuts [4] 57.1 309 178.4 93.4 443 956.3 AQT [8] 38.6 64 56.4 50.1 94 200.2 PQT[9] 35.6 75 29.9 59.6 113 145.6 BV [12] 66.0 68 153.3 64.1 76 2793 Proposed 21.3 47 43.2 34.7 78 182.2 Prop opt 1 17.3 43 43.2 20.1 59 182.2 Prop opt2 12.5 21 43.4 17.9 39 191.7 Sa Samsun msung Ele g Electroni nics
� Performance comparison result for FW types FW1k FW1k FW5k FW5k M M Tavg Tavg Twst Twst Tavg Tavg Twst Twst (Kbyte) (Kbyte) H-trie [1] 52.1 117 39.4 69.2 162 119.1 HiCuts [4] 68.0 342 1373 411.6 1691 3704 AQT [8] 369.3 444 35.2 660.5 1193 479.8 PQT[9] 197.9 293 27.2 571.1 999 136.0 BV [12] 196.6 318 111.9 738.8 1044 2340 Proposed 192.7 293 21.8 560.7 1002 95.6 Prop opt 1 115.9 286 21.8 392.5 971 95.6 Prop opt2 19.3 378 22.1 67.0 804 95.9 Sa Samsun msung Ele g Electroni nics
� Performance comparison result for IPC types IPC1k IP C1k IP IPC5k C5k M M Tavg Tavg Twst Twst Tavg Tavg Twst Twst (Kbyte) (Kbyte) H-trie [1] 71.9 128 121.6 85.6 192 224.7 HiCuts [4] 27.1 147 656.6 103.9 505 3060 AQT [8] 94.5 119 71.2 344.8 415 234.3 PQT[9] 73.6 106 30.9 202.1 295 139.9 BV [12] 63.6 80 154.3 151.9 230 2351 Proposed 63.2 76 53.0 182.3 263 119.3 Prop opt 1 33.4 71 53.0 65.2 233 119.3 Prop opt2 21.9 69 54.6 32.3 234 118.3 Sa Samsun msung Ele g Electroni nics
Sa Samsun msung Ele g Electroni nics
� We proposed an efficient packet classification algorithm which shows excellent performance in the search speed and the required memory size. � We have explored a method to apply the binary search on length for packet classification. � The average number of memory accesses for the proposed algorithm is about 17 for a 5000 rule classifier of ACL type which is much better than related works. Sa Samsun msung Ele g Electroni nics
Recommend
More recommend
